Overview
YAML loader processes YAML files using jq-style queries to split documents and extract content. Supports multiple document files, metadata flattening, and flexible content synthesis modes. Loader Class:YAMLLoader
Config Class: YAMLLoaderConfig
Install
Install the YAML loader optional dependency group:
uv pip install "upsonic[yaml-loader]"
Examples
from upsonic import Agent, Task, KnowledgeBase
from upsonic.loaders.yaml import YAMLLoader
from upsonic.loaders.config import YAMLLoaderConfig
from upsonic.embeddings import OpenAIEmbedding, OpenAIEmbeddingConfig
from upsonic.text_splitter.recursive import RecursiveChunker, RecursiveChunkingConfig
from upsonic.vectordb import ChromaProvider, ChromaConfig, ConnectionConfig, Mode
# Configure loader
loader_config = YAMLLoaderConfig(
split_by_jq_query=".articles[]",
content_synthesis_mode="smart_text",
metadata_jq_queries={"author": ".author", "date": ".published"}
)
loader = YAMLLoader(loader_config)
# Setup KnowledgeBase
embedding = OpenAIEmbedding(OpenAIEmbeddingConfig())
chunker = RecursiveChunker(RecursiveChunkingConfig())
vectordb = ChromaProvider(ChromaConfig(
collection_name="yaml_data",
vector_size=1536,
connection=ConnectionConfig(mode=Mode.IN_MEMORY)
))
kb = KnowledgeBase(
sources=["data.yaml"],
embedding_provider=embedding,
vectordb=vectordb,
loaders=[loader],
splitters=[chunker]
)
# Query with Agent
agent = Agent("anthropic/claude-sonnet-4-5")
task = Task("Find articles about machine learning", context=[kb])
result = agent.do(task)
print(result)
Parameters
| Parameter | Type | Description | Default | Source |
|---|---|---|---|---|
encoding | str | None | File encoding (auto-detected if None) | None | Base |
error_handling | "ignore" | "warn" | "raise" | How to handle loading errors | ”warn” | Base |
include_metadata | bool | Whether to include file metadata | True | Base |
custom_metadata | dict | Additional metadata to include | Base | |
max_file_size | int | None | Maximum file size in bytes | None | Base |
skip_empty_content | bool | Skip documents with empty content | True | Base |
split_by_jq_query | str | jq query to select document objects | ”.” | Specific |
handle_multiple_docs | bool | Process multiple documents separated by ’---‘ | True | Specific |
content_synthesis_mode | "canonical_yaml" | "json" | "smart_text" | Content format | ”canonical_yaml” | Specific |
yaml_indent | int | Indentation level for YAML output | 2 | Specific |
json_indent | int | None | Indentation level for JSON output | 2 | Specific |
flatten_metadata | bool | Flatten nested structure into metadata | True | Specific |
metadata_jq_queries | dict[str, str] | None | Map metadata keys to jq queries | None | Specific |